2.50
Hdl Handle:
http://hdl.handle.net/10033/621355
Title:
The zlog value as a basis for the standardization of laboratory results
Authors:
Hoffmann, Georg; Klawonn, Frank ( 0000-0001-9613-182X ) ; Lichtinghagen, Ralf; Orth, Matthias
Abstract:
Abstract Background: With regard to the German E-Health Law of 2016, the German Society for Clinical Chemistry and Laboratory Medicine (DGKL) has been invited to develop a standard procedure for the storage and transmission of laboratory results. We suggest the commonly used z-transformation. Methods: This method evaluates by how many standard deviations (SDs) a given result deviates from the mean of the respective reference population. We confirm with real data that laboratory results of healthy individuals can be adjusted to a normal distribution by logarithmic transformation. Results: Thus, knowing the lower and upper reference limits LL and UL, one can transform any result x into a zlog value using the following equation: $\eqalign{ {\rm{zlog}} = & {\rm{(log(x)}}-{\rm{(log(LL)}} + {\rm{log(UL))/2)\cdot3}}{\rm{.92/(log(UL)}} \cr -{\bf{ }}{\rm{log(LL))}} \cr} $ The result can easily be interpreted, as its reference interval (RI) is –1.96 to +1.96 by default, and very low or high results yield zlog values around –5 and +5, respectively. For intuitive data presentation, the zlog values may be transformed into a continuous color scale, e.g. from blue via white to orange. Using the inverse function, any zlog value can then be translated into the theoretical result of an analytical method with another RI: (1) $${\rm{x}} = {\rm{L}}{{\rm{L}}^{0.5 - {\rm{zlog}}/3.92}} \cdot {\rm{U}}{{\rm{L}}^{0.5 + {\rm{zlog}}/3.92}}$$ Conclusions: Our standardization proposal can easily be put into practice and may effectively contribute to data quality and patient safety in the frame of the German E-health law. We suggest for the future that laboratories should provide the zlog value in addition to the original result, and that the data transmission protocols (e.g. HL7, LDT) should contain a special field for this additional value.
Affiliation:
Helmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7, 38124 Braunschweig, Germany.
Citation:
The zlog value as a basis for the standardization of laboratory results 2017, 41 (1) LaboratoriumsMedizin
Journal:
LaboratoriumsMedizin
Issue Date:
26-Jan-2017
URI:
http://hdl.handle.net/10033/621355
DOI:
10.1515/labmed-2017-0135
Additional Links:
http://www.degruyter.com/view/j/labm.2017.41.issue-s1/labmed-2017-0135/labmed-2017-0135.xml
Type:
Article
ISSN:
1439-0477; 0342-3026
Appears in Collections:
publications of the research group cellular proteom research (CPRO)

Full metadata record

DC FieldValue Language
dc.contributor.authorHoffmann, Georgen
dc.contributor.authorKlawonn, Franken
dc.contributor.authorLichtinghagen, Ralfen
dc.contributor.authorOrth, Matthiasen
dc.date.accessioned2018-04-16T08:09:36Z-
dc.date.available2018-04-16T08:09:36Z-
dc.date.issued2017-01-26-
dc.identifier.citationThe zlog value as a basis for the standardization of laboratory results 2017, 41 (1) LaboratoriumsMedizinen
dc.identifier.issn1439-0477-
dc.identifier.issn0342-3026-
dc.identifier.doi10.1515/labmed-2017-0135-
dc.identifier.urihttp://hdl.handle.net/10033/621355-
dc.description.abstractAbstract Background: With regard to the German E-Health Law of 2016, the German Society for Clinical Chemistry and Laboratory Medicine (DGKL) has been invited to develop a standard procedure for the storage and transmission of laboratory results. We suggest the commonly used z-transformation. Methods: This method evaluates by how many standard deviations (SDs) a given result deviates from the mean of the respective reference population. We confirm with real data that laboratory results of healthy individuals can be adjusted to a normal distribution by logarithmic transformation. Results: Thus, knowing the lower and upper reference limits LL and UL, one can transform any result x into a zlog value using the following equation: $\eqalign{ {\rm{zlog}} = & {\rm{(log(x)}}-{\rm{(log(LL)}} + {\rm{log(UL))/2)\cdot3}}{\rm{.92/(log(UL)}} \cr -{\bf{ }}{\rm{log(LL))}} \cr} $ The result can easily be interpreted, as its reference interval (RI) is –1.96 to +1.96 by default, and very low or high results yield zlog values around –5 and +5, respectively. For intuitive data presentation, the zlog values may be transformed into a continuous color scale, e.g. from blue via white to orange. Using the inverse function, any zlog value can then be translated into the theoretical result of an analytical method with another RI: (1) $${\rm{x}} = {\rm{L}}{{\rm{L}}^{0.5 - {\rm{zlog}}/3.92}} \cdot {\rm{U}}{{\rm{L}}^{0.5 + {\rm{zlog}}/3.92}}$$ Conclusions: Our standardization proposal can easily be put into practice and may effectively contribute to data quality and patient safety in the frame of the German E-health law. We suggest for the future that laboratories should provide the zlog value in addition to the original result, and that the data transmission protocols (e.g. HL7, LDT) should contain a special field for this additional value.en
dc.relation.urlhttp://www.degruyter.com/view/j/labm.2017.41.issue-s1/labmed-2017-0135/labmed-2017-0135.xmlen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.titleThe zlog value as a basis for the standardization of laboratory results-
dc.typeArticleen
dc.contributor.departmentHelmholtz-Zentrum für Infektionsforschung GmbH, Inhoffenstr. 7, 38124 Braunschweig, Germany.en
dc.identifier.journalLaboratoriumsMedizinen
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